2015
DOI: 10.1016/j.im.2014.11.003
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A method for identifying journals in a discipline: An application to information systems

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Cited by 14 publications
(18 citation statements)
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References 32 publications
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“…First, our study demonstrated that a country's degree centrality positively affected its citation counts, which is consistent with prior research (Yan and Ding 2009;Oguz, Kinglsey and John 2014;Chan, Guness and Kim 2015). This finding enriches our understanding about countries' citation counts or research impact in a discipline.…”
Section: Discussionsupporting
confidence: 90%
“…First, our study demonstrated that a country's degree centrality positively affected its citation counts, which is consistent with prior research (Yan and Ding 2009;Oguz, Kinglsey and John 2014;Chan, Guness and Kim 2015). This finding enriches our understanding about countries' citation counts or research impact in a discipline.…”
Section: Discussionsupporting
confidence: 90%
“…for the publication be considered in the category, which is why the cut-off point is set at 25% (coinciding with the classification of pure and hybrid publications made by Chan, Guness and Kim (2015)) and excluding the 11 journals and congresses that are not related to the theme. With this, there are 82 journals and 137 congresses (Annex 1) to be analyzed in comparison to the global map of science.…”
Section: Resultsmentioning
confidence: 99%
“…Broadly, the intellectual field of any research domain is mapped by SNA of citation, and co-citation networks (Giannakis, 2012;Wang & Bowers, 2016). It helps to determine influential journals, relationship among them (Polites & Watson, 2009) and their impact (Chuan, Guness, & Kim, 2015;Wang & Bowers, 2016), identify core, most-cited text and influential researchers, highlight gaps in particular research area (Peng, Zhang, Zhong, & Zhu, 2013;Schmidt et al, 2015), and examine whether members of a particular research community share a common social identity (Vidgen et al, 2007;Xu & Chau, 2006). Further, SNA is used with other text mining (Burgess, Grimshaw, & Shaw, 2017), and data reduction approaches to examine identity, diversity, cohesion, and fragmentation in a particular research field (Burgess et al, 2017;Polites & Watson, 2009;Vessey et al, 2002).…”
Section: Methods and Datamentioning
confidence: 99%